New Hours-of-Service Rules: Trucking Industry Reactions and Safety Outcomes

Dick, Virginia Robinson; Hendrix, James W.; Knipling, R R

doi:10.3141/1966-13

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Non-crash injuries are a key focal point for driver health protection, as they are far more prevalent than injuries sustained from crashes [86]. OSHA has a limited role in protecting drivers against non-crash injuries, and training and safety management within companies have similarly fallen short in protecting drivers [72].…”

Section: Non-crash Injuries and Ergonomicsmentioning

confidence: 99%

Risks Endemic to Long-Haul Trucking in North America: Strategies to Protect and Promote Driver Well-Being

Apostolopoulos¹,

Lemke²,

Sönmez³

2014

New Solut

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Long-haul truck drivers in North America function in a work context marked by excess physical and psychological workload, erratic schedules, disrupted sleep patterns, extreme time pressures, and these factors' far-reaching consequences. These work-induced stressors are connected with excess risk for cardiometabolic disease, certain cancers, and musculoskeletal and sleep disorders, as well as highway crashes, which in turn exert enormous financial burdens on trucking and warehousing companies, governments and healthcare systems, along with working people within the sector. This article: 1) delineates the unique work environment of long-haul truckers, describing their work characteristics and duties; (2) discusses the health hazards of long-haul trucking that impact drivers, the general population, and trucking enterprises, examining how this work context induces, sustains, and exacerbates these hazards; and (3) proposes comprehensive, multi-level strategies with potential to protect and promote the health, safety, and well-being of truckers, while reducing adverse consequences for companies and highway safety.

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Section: Non-crash Injuries and Ergonomicsmentioning

confidence: 99%

Risks Endemic to Long-Haul Trucking in North America: Strategies to Protect and Promote Driver Well-Being

Apostolopoulos¹,

Lemke²,

Sönmez³

2014

New Solut

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“…Few studies have focused on the effects of this restart. Drivers like to use it, but it may force them to spend less time at home (22). For truckload carriers, a 34-h restart significantly affects their employees' available time (Figure 1, c, d, e, and i).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Machine Learning for Recognizing Driving Patterns of Drivers of Large Commercial Trucks

Chen

Xie

2015

Transportation Research Record: Journal of the Transportation R

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Commercial large truck crashes are more likely to involve fatalities and significant costs than passenger vehicle crashes are. To reduce fatigue-related crashes of large trucks caused by drivers' irregular work schedules, FMCSA has enforced hours-of-service rules to regulate the activities of drivers of commercial large trucks. The complex influence of drivers' multiday driving activity patterns on crash risk was examined with data collected from two national truckload carriers. A machine learning approach, k-means clustering, was used to classify large truck drivers into 10 clusters according to their 15-min driving activities over multiple days. Then, the crash risk and driving activity pattern were identified for each cluster. Discrete-time logistic regression models were used to quantify the relationships between driving activity patterns and crash risk. Results indicated that the driving pattern with the lowest crash risk could be daytime driving between 4:00 a.m. and noon, with rest breaks in the late afternoon (4:00 to 6:00 p.m.). Drivers with high proportions of afternoon on-duty time after a long off-duty period experienced significantly higher crash risk. A representative day concept is proposed as a complementary method to identify relationships between driving patterns and crash risk. Moreover, on-duty hours can be a useful indicator of crash risk for drivers of large trucks. High proportions of on-duty hours in the early morning and late afternoon often are associated with high crash risk.

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“…(15,16) Reportable crashes were collected and analyzed. (A reportable crash involves a fatality, an injury requiring medical treatment away from the scene of the crash, or a towaway).…”

Section: Driving Hour and Time-on-taskmentioning

confidence: 99%

The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations

Blanco¹,

Hanowski²,

Olson³

et al. 2011

PsycEXTRA Dataset

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FOREWORDThe work performed under this project included a literature review of topics related to commercial motor vehicle driver fatigue (including topics of work hours, driving time, duty periods, and restart/recovery periods) published between 2006 and July 2010. The research also included an assessment of the tasks drivers perform in a typical workday. In addition, analyses were conducted to determine the impact of driving hours, work hours, and breaks on driving performance. NOTICEThis document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for its contents or the use thereof.The contents of this Report reflect the views of the contractor, who is responsible for the accuracy of the data presented herein. The contents do not necessarily reflect the official policy of the Department of Transportation.This Report does not constitute a standard, specification, or regulation.The United States Government does not endorse products or manufacturers named herein. Trade or manufacturers' names appear herein only because they are considered essential to the objective of this document. Current hours-of-service (HOS) regulations prescribe limits to commercial motor vehicle (CMV) drivers' operating hours. Besides assessing activities performed in the 14-hour workday, the relationship between safety-critical events (SCEs) and driving hours, work hours, and breaks was investigated. The data used in the analyses were collected in the Naturalistic Truck Driving Study and included 97 drivers and about 735,000 miles of continuous driving data. The assessment of the drivers' workday determined that, on average, drivers spent 66 percent of their shift driving, 23 percent in non-driving work, and 11 percent resting. Analyses on driving hours (i.e., driving only) and SCE risk found a time-on-task effect across hours. Analyses on work hours (i.e., driving in addition to non-driving work) found that risk of being involved in an SCE increased as work hours increased. This suggests that time-on-task effects may not be related to driving hours alone, but implies an interaction between driving hours and work hours: if a driver begins the day with several hours of non-driving work, followed by driving that goes deep into the 14-hour workday, SCE risk was found to increase. The finding from the workday characterization that drivers spent approximately 23 percent of their workday performing non-driving work provides a possible explanation for this time-on-task effect across work hours. Breaks from driving were found to be beneficial in reducing SCEs (during 1-hour window after a break) and were effective to counteract the negative effects of time-on-task. TECHNICAL REPORT DOCUMENTATION PAGE17.

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New Hours-of-Service Rules: Trucking Industry Reactions and Safety Outcomes

Cited by 3 publications

References 4 publications

Risks Endemic to Long-Haul Trucking in North America: Strategies to Protect and Promote Driver Well-Being

Risks Endemic to Long-Haul Trucking in North America: Strategies to Protect and Promote Driver Well-Being

Machine Learning for Recognizing Driving Patterns of Drivers of Large Commercial Trucks

The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations

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